Triple

T2142409
Position Surface form Disambiguated ID Type / Status
Subject Yatesville, Georgia E46787 entity
Predicate hasName P744 FINISHED
Object Yatesville, Georgia E46787 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Yatesville, Georgia | Statement: [Yatesville, Georgia, hasName, Yatesville, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yatesville, Georgia
Context triple: [Yatesville, Georgia, hasName, Yatesville, Georgia]
  • A. Yatesville, Georgia chosen
    Yatesville, Georgia is a small rural town in Upson County known for its quiet community character and location in central Georgia.
  • B. Luthersville, Georgia
    Luthersville, Georgia is a small incorporated city in west-central Georgia that serves as one of the primary communities within Meriwether County.
  • C. Fairburn, Georgia
    Fairburn, Georgia is a small city in the Atlanta metropolitan area known for its historic downtown and role as a growing suburban community.
  • D. Grantville, Georgia
    Grantville, Georgia is a small city in west-central Georgia known for its historic downtown and role as a filming location for several movies and television shows.
  • E. Woodbury, Georgia
    Woodbury, Georgia is a small city in Meriwether County known for its rural character and historic railroad and agricultural roots in west-central Georgia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe0543108190862dd9a4a861c758 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51b63e4081908a5d87af5d17d3c4 completed March 9, 2026, 4:51 a.m.
Created at: March 4, 2026, 7:44 p.m.